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cs.AI2026
OOD-MMSafe: Advancing MLLM Safety from Harmful Intent to Hidden Consequences
Ming Wen, Kun Yang, Jingyu Zhang +4
While safety alignment for Multimodal Large Language Models (MLLMs) has gained significant attention, current paradigms primarily target malicious intent or situational violations.…
cs.AI2026
CSR-Bench: A Benchmark for Evaluating the Cross-modal Safety and Reliability of MLLMs
Yuxuan Liu, Yuntian Shi, Kun Wang +2
Multimodal large language models (MLLMs) enable interaction over both text and images, but their safety behavior can be driven by unimodal shortcuts instead of true joint intent un…